Calorie Burn Predection using Machine Learning

Abstract: In today's world, people are having very tight schedules due to the changes in their lifestyles and work commitments. But it requires regular physical activity to stay fit and healthy. People do not concentrate on their food habits, leading to obesity. Obesity is becoming a major and common problem in today's lifestyle. This leads people to choose their diet and do an equal amount of exercise to stay fit and healthy. The main part here is people should have adequate knowledge about their calorie intake and burn, keeping a track of their calorie intake is easy as it's available on the product label or on the internet. Keeping track of calories burnt is a difficult part as there are very few devices for that. Calories burned by an individual are based on MET charts and formulas. The main agenda of this study is a prediction of the burnt calories with the help of an XG boost regression model as the ML (machine learning) algorithm to show accurate results. The model is fed with more than 15,000 data and its mean absolute error is 2.7 which will become better over time by feeding the XG boost regression model with more data.